code: def _d_per_head_conv_mha(c: TransformerConfigs):
      """
      Add the [option](https://docs.labml.ai/api/configs.html#labml.configs.option)
       of [**Multi Depth-wise Per Head Conv Head Attention**](variation.html) to
       [configurable transformer](../configs.html#TransformerConfigs)
  
      📝 *This is a variation we tried*
      """
      from labml_nn.transformers.primer_ez.variations import (
          MultiDPHConvHeadAttention,
      )
  
      return MultiDPHConvHeadAttention(
          c.n_heads, c.d_model, dropout_prob=c.dropout
      )
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/primer_ez/experiment.py
imports: from labml import experiment
  from labml.configs import option
  from labml_nn.transformers import TransformerConfigs
  from labml_nn.transformers.basic.autoregressive_experiment import Configs
  from labml_nn.transformers.configs import FeedForwardConfigs
  from labml_nn.transformers.primer_ez import SquaredReLU
label_desc: Use image node_id 4 for calling a global function with example usage: _d_per_head_conv_mha(c) and returns: MultiDPHConvHeadAttention